It is axiomatic that consumers will tend to spend more when they have greater purchasing power. The capability to accurately estimate a consumer's risk of default may allow a financial institution (such as a credit company, lender or any consumer services companies) to better target potential prospects and identify any opportunities to increase consumer transaction volumes, without an undue increase in the risk of defaults. Attracting additional consumer spending, in turn, would often increase such financial institution's revenues, primarily in the form of an increase in transaction fees and interest payments received. Consequently, a consumer model that can accurately estimate risk of default is of paramount interest to many financial institutions and other consumer services companies.
Sufficient systems are not available for appropriately estimating a consumer's risk of default. The existing system typically includes limited and incomplete consumer information from credit bureaus and the like at the aggregate and individual consumer levels. In order to achieve a more complete picture of a consumer's risk of default, one must examine in detail a larger range of a consumer's financial accounts, including credit accounts, checking and savings accounts, investment portfolios, and the like. However, the vast majority of consumers do not maintain all such accounts with the same financial institution and access to detailed financial information from other financial institutions is restricted by consumer privacy laws, disclosure policies and security concerns.
Accordingly, there is a need for a system and method for suitably modeling a consumer's risk of default which addresses certain problems of existing technologies.